一。思路
二。代码：
#coding:utf-8
import numpy as np
import PIL.Image as Image
import pickle as p
import os
class ImageTools(object):
image_dir='images/'
result_dir='results/'
data_file_path='data.bin'
def imageToArray(self,files):
images=[]
for i in range(len(files)):
image=Image.open(ImageTools.image_dir+files[i])
r,g,b= image.split()
r_array = np.array(r).reshape(62500)
g_array = np.array(g).reshape(62500)
b_array = np.array(b).reshape(62500)
image_arry = np.concatenate((r_array,g_array,b_array))
images=np.concatenate((images,image_arry))
print(images.shape)
images =np.array(images).reshape((len(files),(3*62500)))
print(images.shape)
f =open(ImageTools.data_file_path,'wb')
p.dump(images,f)
f.close()
def readToImage(self,file):
f = open(file,'rb')
arr = p.load(f) # 30行，187500列
rows = arr.shape[0]
new_arr =arr.reshape((rows,3,250,250)) # 把矩阵变成一个高维矩阵
for i in range(rows):
r =Image.fromarray(new_arr[i][0]).convert("L") #把每个图片中RGB通道分离
g =Image.fromarray(new_arr[i][1]).convert("L") #把每个图片中RGB通道分离
b =Image.fromarray(new_arr[i][2]).convert("L") #把每个图片中RGB通道分离
image = Image.merge("RGB",(r,g,b)); # 合并RGB通道获得一张图片
# f =open(ImageTools.result_dir+str(i)+'.png','wb')
image.save(ImageTools.result_dir+str(i)+'.png',"png")
if __name__=="__main__":
it = ImageTools()
files= os.listdir(ImageTools.image_dir)
# it.imageToArray(files)
it.readToImage('data.bin')
